Presenting a Dynamic Model of Manpower Demand in the Tax Affairs Organization of Iran

محورهای موضوعی : Agriculture Marketing and Commercialization

Arash Rouhani ¹ (Department of Management, Rafsanjan Branch, Islamic Azad University, Rafsanjan, Iran)
Malikeh Beheshtifar ² (Department of Management, Rafsanjan Branch, Islamic Azad University, Rafsanjan, Iran)
Hossein Kazemi ³ (Department of Public Administration, Vali-e-Asr University, Rafsanjan, Iran)

تاریخ دریافت : 1400/07/12 تاریخ پذیرش : 1400/12/04 تاریخ انتشار : 1401/03/11

کلید واژه: Experts, Fuzzy DEMATEL, Dynamic Model, Delphi method, Manpower Demand,

چکیده مقاله :

Providing qualified human resources is one of the main issues of today's organizations. Since the Tax Affairs Organization of Iran is a governmental and specialized organization, so the manpower required by the organization; In terms of having special features needs time; is not available to the organization, which makes planning to anticipate manpower demand inevitable. The main purpose of this study is to provide a dynamic model for manpower demand in the Tax Affairs Organization of Iran, as an effective device for financing the country. In the present study, an attempt has been made to dynamically model the demand for manpower using the data obtained from the Delphi and Fuzzy DEMATEL methods, through the systems dynamics method. In this study, 9 effective endogenous and exogenous factors were localized and selected by the Delphi method by experts. Then the Fuzzy DEMATEL method was used to determine the relationships, intensity, and effectiveness, and finally, the dynamic research model in addition to possible scenarios is expressed.

منابع و مأخذ:

• Koltnerová K. & Chlpeková A. & Samáková J. (2013), The Importance of Human Resource Planning in Industrial Enterprises, Research Papers Faculty of Materials Science and Technology Slovak University of Technology, 20(1): 62-71.


• Mohammadi J. & Fakher I. (2011), Prediction of supply and demand of specialized manpower using Box–Jenkins methodology, Journal of Human Development, 6(2): 175-200.


• Slangen B. (2020), Dynamic human resource management decision support model, International Journal of Computer Science & Information Technology (IJCSIT), 13(4): 2-10.


• Ivan B. & Turyareeba D. & Wagima C. & Wemesa R. & Ssebbaale E. & Moses K. (2020), Human Resource Planning Process and Its Influence to the Performance of Health Sector in Uganda: A Case Study of International Hospital Kampala (IHK), Open Journal of Business and Management, 8(5): 2248-2261.


• Mashayekhi A. (2018), System dynamics, Tehran: Aryana Ghalam Publications, 1: 18-29.


• Ghimire B. (2020), Human Resource Planning Presented by: Binod Ghimire, May, 31-37.


• Adisak C. (2015), The Development of Manpower Modeling & Optimization: A Case Study on Asia Leading Energy Conglomerates, Global Journal of Human Resource Management, 6(1): 34-43.


• Aburawi I. & Hafeez K. (2009), Managing Dynamics of Human Resource And Knowledge Management In Organizations Through System Dynamics Modelling, International Journal of Sciences And Techniques of Automatic Control & Computer Engineering, 16(4): 1108-1125


• Dalalah D. & Bataineh O. (2009), A fuzzy logic approach to the selection of the best silicon crystal slicing technology, Expert Syst. Appl, 3(6): 3712-3719.


• Ricciardi F. & De Bernardi P. & Cantino V. (2020), System dynamics modeling as a circular process: The smart commons approach to impact management, Technological Forecasting and Social Change, 15(1): 107-119.


• Gao W. & Hong B. & Swaney D. & Whoarth R. & Gua H. (2016). A system dynamics model for managing regional N inputs fromhuman activities, Ecological Modelling, 15(3): 82-91.


• Merkac M. & Zoroja J. (2013), Simulation Modelling Approach to Human Resources Management: Burnout Effect Case Study, University of Zagreb, 3: 63-70.


• Pejic Bach M. & Tustanovski E. & Ip A. & Yung K. & Roblek V. (2019), System dynamics models for the simulation of sustainable urban development: A review and analysis and the stakeholder perspective, Kybernetes, 49(2): 460-504.


• Choudhari S. & Gajjar H. (2018), Simulation modeling for manpower planning in electrical maintenance service facility, Business Process Management Journal, 24(1): 89-104.


• Jiawei Y. (2010), modelling and Planning of Manpower Supply and demand, National University of Singapore, 3: 145-154.


• Ulferts G. & Wirtz P. & Peterson E. (2009), Strategic Human Resource Planning in Academia, American Journal of Business Education (AJBE), 2(7): 1-10.


• Norcliffe A. & Hafeez K. & Aburawi I. (2004), Human Resource Modelling Using System Dynamics, 22nd International Conference of System Dynamics Society, Oxford, 2: 44-58.


• Bashan V. & Demirel H. (2018), Application of Fuzzy Dematel Technique to Assess Most Common Critical Operational Faults of Marine Boilers, Journal of Polytechnic, 22(3): 545-555.


• Gao S. & Chen li-shan C. (2018), A Fuzzy DEMATEL method for analyzing key factors of the product promotion, Journal of Discrete Mathematical Sciences & Cryptography, 21(6): 1225-1228.


• Fu X. & Wang N. & Jiang S. & Yang F. & Li J. & Wang C. (2019), A research on influencing factors on the international cooperative exploitation for deep-sea bioresources based on the ternary fuzzy DEMATEL method, Ocean and Coastal Management, 17(2): 55-63.


• Seker S. & Zavadskas EK. (2017), Application of Fuzzy DEMATEL Method for Analyzing Occupational Risks on Construction Sites, sustainability publication, 1-19.


• Mahmoudi S. & Jalali A. & Ahmadi M. & Abasi P. & Salari N. (2019), Identifying critical success factors in Heart Failure Self-Care using fuzzy DEMATEL method, Applied Soft Computing Journal, 84(1): 105-109.


• Si S. & You X. & Liu H. & Zhang P. (2018), DEMATEL Technique: A Systematic Review of the State-of-the-Art Literature on Methodologies and Applications, Mathematical Problems in Engineering, 1: 119-128.


• Farooque M. & Jain V. & Zhang A. & Li Z. (2020), Fuzzy DEMATEL analysis of barriers to Blockchain-based life cycle assessment in China. Computers and Industrial Engineering, 14(7): 106-117.


• Shah Moradi M. & Salajegheh S. & Amiri A. & Pourkiani M. & Sheykhi A. (2020), Identifying the Indicators and Components of Human Resource Management Based on Knowledge Management and Prioritizing Them in the Executive Organs of the City of Sari. Agricultural Marketing and Commercialization Journal, 4(1): 38-50.


• Shepherd S. (2014). A review of system dynamics models applied in transportation, White Rose Research Online, 2: 41-48.


• Samara E. & Geordidadis P. & Bakouros I. (2012), the impact of innovation policies on the performance of national innovation systems: A system dynamics analysis, Technovation, 624-638


• Jafari M. & Hesam Amiri R. & Bourouni A. (2008), An Interpretive Approach to Drawing Causal Loop Diagrams, Department of Industrial Engineering, Iran University of Science and Technology, 2: 24-33.


• Enshaei H. & Manzari Tavakoli H. & Salajegheh S. & Pourkiani M. & Babaei H. (2020), Presenting A Model of the Social Factors Effective in the Service Quality of the Municipalities of Mazandaran, Agricultural Marketing and Commercialization Journal, 4(1): 60-76.


• Chaker F. & El Manouar A. (2015), Towards A System Dynamics Modeling Method Based on Dematel, International Journal of Computer Science & Information Technology (IJCSIT), 7(2): 27-40.